library(here)
## here() starts at /home/natasa/Desktop/master_project/Master-Project-Natasa-Mortvanski
library(phyloseq)
library(qiime2R)
library(microbiome)
## Loading required package: ggplot2
##
## microbiome R package (microbiome.github.com)
##
##
##
## Copyright (C) 2011-2021 Leo Lahti,
## Sudarshan Shetty et al. <microbiome.github.io>
##
## Attaching package: 'microbiome'
## The following object is masked from 'package:ggplot2':
##
## alpha
## The following object is masked from 'package:base':
##
## transform
library(microbiomeutilities)
## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## Warning: replacing previous import 'ggplot2::alpha' by 'microbiome::alpha' when
## loading 'microbiomeutilities'
library(tidyr)
library(data.table)
##
## Attaching package: 'data.table'
## The following objects are masked from 'package:dplyr':
##
## between, first, last
library(corrplot)
## corrplot 0.92 loaded
library(flextable)
library(writexl)
# Creating phyloseq object
physeq <- qza_to_phyloseq(
features= "~/Desktop/master_project/Data_Hospital_donors/R2960/SCFA_QIIME2_analysis/table-dada2.qza",
tree= "~/Desktop/master_project/Data_Hospital_donors/R2960/SCFA_QIIME2_analysis/rooted-tree.qza",
taxonomy= "~/Desktop/master_project/Data_Hospital_donors/R2960/SCFA_QIIME2_analysis/taxonomy.qza",
metadata = "~/Desktop/master_project/Master-Project-Natasa-Mortvanski/01_tidy_data/SCFA_alpha_donors.tsv"
)
# tax_glom function merges species that have the same taxonomy at a certain
# taxonomic rank - in this case family level
glom <- tax_glom(physeq, taxrank=rank_names(physeq)[5])
# psmelt function melts phyloseq data object into large data.frame
smelted_data <- psmelt(glom)
abundances_fam <- smelted_data %>% select(-c(Kingdom, Phylum, Class, Order)) %>%
spread(Family, Abundance) %>%
group_by(Sample) %>%
summarize(across(3:63, ~unique(na.omit(.x))),.groups = 'drop')
abundances_fam
## # A tibble: 104 × 62
## Sample donor_donation acetic_acid propionic_acid butyric_acid shannon_entropy
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 A1-Pl… CGR32F_7th 336. 77.3 75.8 6.81
## 2 A10-P… CLA33F_11th 177. 60.3 163. 6.63
## 3 A11-P… MBD34F_3rd 43.7 22.8 24.1 7.18
## 4 A12-P… FBG21M_4th 187. 46.0 42.6 6.69
## 5 A2-Pl… RTF49M_4th 52.3 14.2 16.1 6.86
## 6 A3-Pl… SMP48F_6th 47.0 18.6 17.6 6.65
## 7 A3-Pl… RTF49M_10th 369. 131. 87.1 6.42
## 8 A4-Pl… RTF49M_15th 131. 36.4 82.1 6.52
## 9 A5-Pl… EDR39F_1st 126. 67.1 57.8 6.36
## 10 A6-Pl… ATH27F_1st 67.0 32.3 25.3 6.82
## # ℹ 94 more rows
## # ℹ 56 more variables: chao1 <dbl>, fisher_alpha <dbl>, margalef <dbl>,
## # gini_index <dbl>, menhinick <dbl>, strong <dbl>, simpson <dbl>,
## # faith_pd <dbl>, pielou_evenness <dbl>, `[Barnesiellaceae]` <dbl>,
## # `[Cerasicoccaceae]` <dbl>, `[Mogibacteriaceae]` <dbl>,
## # `[Odoribacteraceae]` <dbl>, `[Paraprevotellaceae]` <dbl>,
## # `[Tissierellaceae]` <dbl>, Alcaligenaceae <dbl>, …
write.table(abundances_fam, file = here("01_tidy_data", "abundance_family.tsv"), row.names=FALSE, sep="\t", quote=FALSE)
# Save results as data frame
tax_alpha_cor <- as.data.frame(cor(abundances_fam[, c(6:15)], abundances_fam[,c(16:50)]))
tax_alpha_cor %>% tibble::rownames_to_column() %>% flextable()
rowname | [Barnesiellaceae] | [Cerasicoccaceae] | [Mogibacteriaceae] | [Odoribacteraceae] | [Paraprevotellaceae] | [Tissierellaceae] | Alcaligenaceae | Anaeroplasmataceae | Bacteroidaceae | Bifidobacteriaceae | Campylobacteraceae | Carnobacteriaceae | Christensenellaceae | Clostridiaceae | Coriobacteriaceae | Dehalobacteriaceae | Desulfovibrionaceae | Elusimicrobiaceae | Enterobacteriaceae | Enterococcaceae | Erysipelotrichaceae | Eubacteriaceae | Fusobacteriaceae | Gemellaceae | Lachnospiraceae | Lactobacillaceae | Leptotrichiaceae | Leuconostocaceae | Methanobacteriaceae | mitochondria | Moraxellaceae | Oxalobacteraceae | Pasteurellaceae | Peptococcaceae | Peptostreptococcaceae |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
shannon_entropy | 0.1961739 | 0.04587657 | 0.42021153 | 0.35326132 | -0.10191302 | 0.15721016 | 0.012886096 | 0.01560096 | -0.10401313 | 0.11404702 | -0.13617509 | 0.08882543 | 0.38080772 | 0.047159992 | 0.21751498 | 0.16634117 | 0.48943128 | 0.0001774658 | -0.2906366 | 0.11363339 | 0.00382816 | 0.04727198 | 0.09246265 | 0.05074282 | 0.110241368 | 0.05627490 | 0.01477416 | 0.036780567 | 0.42413481 | -0.108218796 | 0.036780567 | 0.3966001 | 0.035661043 | 0.22682347 | -0.04046494583 |
chao1 | 0.3983393 | 0.06216873 | 0.44673458 | 0.57132712 | -0.11927104 | 0.09062786 | -0.015945179 | -0.08900386 | 0.06078133 | 0.14902624 | -0.05413649 | 0.06547280 | 0.44115957 | 0.047179832 | 0.25969848 | 0.21082246 | 0.54066280 | 0.0755030083 | -0.3274936 | 0.12923304 | -0.13100630 | -0.01609057 | 0.03090747 | 0.01174541 | 0.010581630 | 0.14336458 | -0.02351381 | 0.042111939 | 0.38925318 | 0.014068695 | 0.042111939 | 0.5081410 | -0.003174261 | 0.29422608 | -0.00224146078 |
fisher_alpha | 0.3936996 | 0.07091003 | 0.44612542 | 0.57158136 | -0.13397330 | 0.09686233 | -0.019397709 | -0.09423500 | 0.05442319 | 0.14663316 | -0.05118035 | 0.06909077 | 0.45375083 | 0.046097431 | 0.26354678 | 0.21765952 | 0.55212263 | 0.0624132416 | -0.3438112 | 0.13301278 | -0.13194528 | -0.01817683 | 0.03711979 | 0.01023980 | 0.009574233 | 0.14914291 | -0.02197679 | 0.028522431 | 0.40319678 | -0.005772743 | 0.028522431 | 0.5168397 | -0.009185043 | 0.30244158 | -0.00001874811 |
margalef | 0.3973124 | 0.06998401 | 0.44809716 | 0.57010029 | -0.13619450 | 0.09749610 | -0.015737951 | -0.09103355 | 0.05468808 | 0.15119899 | -0.04968787 | 0.06813527 | 0.45133338 | 0.050852669 | 0.26443582 | 0.21862052 | 0.55128947 | 0.0643366351 | -0.3459213 | 0.13466851 | -0.13082091 | -0.01606918 | 0.03958950 | 0.01256500 | 0.012095435 | 0.15189829 | -0.01941388 | 0.030786743 | 0.39658681 | -0.005341178 | 0.030786743 | 0.5137065 | -0.010093940 | 0.29894245 | -0.00058696851 |
gini_index | -0.2744844 | -0.07061008 | -0.43738143 | -0.47112177 | 0.12565482 | -0.15186035 | -0.001674808 | 0.01691102 | 0.03200879 | -0.11179463 | 0.09933723 | -0.08644533 | -0.40048430 | -0.048434934 | -0.23175553 | -0.16334157 | -0.50953966 | 0.0151382790 | 0.3085910 | -0.10099551 | 0.02995650 | -0.03869648 | -0.06774699 | -0.04648364 | -0.109638267 | -0.06992236 | 0.00722504 | -0.026077484 | -0.46017354 | 0.097291881 | -0.026077484 | -0.4275486 | -0.021119345 | -0.26707969 | 0.01824285052 |
menhinick | 0.3973124 | 0.06998401 | 0.44809716 | 0.57010029 | -0.13619450 | 0.09749610 | -0.015737951 | -0.09103355 | 0.05468808 | 0.15119899 | -0.04968787 | 0.06813527 | 0.45133338 | 0.050852669 | 0.26443582 | 0.21862052 | 0.55128947 | 0.0643366351 | -0.3459213 | 0.13466851 | -0.13082091 | -0.01606918 | 0.03958950 | 0.01256500 | 0.012095435 | 0.15189829 | -0.01941388 | 0.030786743 | 0.39658681 | -0.005341178 | 0.030786743 | 0.5137065 | -0.010093940 | 0.29894245 | -0.00058696851 |
strong | 0.2838715 | 0.06257516 | 0.15721202 | 0.26712286 | -0.01478512 | -0.05060710 | -0.049059400 | -0.13562485 | 0.11517395 | 0.11523776 | 0.10206079 | 0.01395815 | 0.23867993 | -0.017552577 | 0.14899240 | 0.19784778 | 0.24840376 | 0.2308996280 | -0.1147883 | 0.11663887 | -0.18732150 | -0.14083349 | -0.01563013 | -0.08508918 | -0.292377731 | 0.17218141 | -0.01629158 | 0.019243860 | -0.01445655 | 0.193130418 | 0.019243860 | 0.2829366 | -0.053582330 | 0.16556683 | 0.03796192806 |
simpson | -0.1482763 | -0.02576009 | 0.22892981 | -0.09787139 | 0.02939851 | 0.14114608 | 0.018318426 | 0.10745850 | -0.29376183 | 0.02676426 | -0.24701477 | 0.08533862 | 0.21786878 | -0.012874742 | 0.09241626 | 0.08488361 | 0.27291167 | -0.0152780533 | -0.1015751 | 0.07548602 | 0.12344614 | 0.06359883 | 0.11583283 | 0.04800740 | 0.103548997 | -0.05713842 | 0.04775054 | 0.035672617 | 0.29645593 | -0.125998887 | 0.035672617 | 0.1856331 | 0.094908668 | 0.05686916 | -0.09389218815 |
faith_pd | 0.2845479 | 0.11051965 | 0.40234176 | 0.37278714 | 0.02526113 | 0.11640291 | -0.137494964 | -0.12712645 | -0.03442883 | 0.20266925 | -0.02828822 | 0.04559428 | 0.44693338 | 0.008489347 | 0.35554525 | 0.15031176 | 0.47533031 | 0.1585353280 | -0.1709059 | 0.15630988 | -0.04031295 | -0.03580521 | 0.03968340 | -0.03134623 | -0.234888894 | 0.08073983 | -0.06119944 | -0.054986273 | 0.35482468 | 0.528622964 | -0.054986273 | 0.3597795 | -0.136334961 | 0.31505715 | -0.04653492509 |
pielou_evenness | -0.3778888 | -0.04163143 | -0.03466668 | -0.36034803 | 0.06859167 | 0.11427413 | 0.024317169 | 0.16931815 | -0.30487484 | -0.09177427 | -0.18934919 | 0.04902762 | -0.07733878 | -0.041278643 | -0.07766181 | -0.08720601 | -0.07324653 | -0.1315143919 | 0.0867717 | -0.03802944 | 0.23102940 | 0.10166737 | 0.08480880 | 0.05452080 | 0.166035449 | -0.18446494 | 0.04095021 | -0.003949148 | 0.13015699 | -0.200237211 | -0.003949148 | -0.1521718 | 0.085048126 | -0.09477153 | -0.07529454866 |
# Plot correlation
matrix_tax_alpha <- cor(abundances_fam[, c(6:15)], abundances_fam[,c(16:50)] , method = "spearman")
corrplot(matrix_tax_alpha, method="circle", tl.col = "black", tl.srt = 90, col.lim = c(-1,1), insig = "blank")
library(dichromat)
library(RColorBrewer)
library(graphics)
# Save results as data frame
tax_SCFA_cor <- as.data.frame(cor(abundances_fam[, c(3:5)], abundances_fam[,c(16:50)]))
tax_SCFA_cor %>% tibble::rownames_to_column() %>% flextable()
rowname | [Barnesiellaceae] | [Cerasicoccaceae] | [Mogibacteriaceae] | [Odoribacteraceae] | [Paraprevotellaceae] | [Tissierellaceae] | Alcaligenaceae | Anaeroplasmataceae | Bacteroidaceae | Bifidobacteriaceae | Campylobacteraceae | Carnobacteriaceae | Christensenellaceae | Clostridiaceae | Coriobacteriaceae | Dehalobacteriaceae | Desulfovibrionaceae | Elusimicrobiaceae | Enterobacteriaceae | Enterococcaceae | Erysipelotrichaceae | Eubacteriaceae | Fusobacteriaceae | Gemellaceae | Lachnospiraceae | Lactobacillaceae | Leptotrichiaceae | Leuconostocaceae | Methanobacteriaceae | mitochondria | Moraxellaceae | Oxalobacteraceae | Pasteurellaceae | Peptococcaceae | Peptostreptococcaceae |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
acetic_acid | 0.20524171 | -0.09267731 | -0.06139248 | 0.17632447 | 0.0408958294 | -0.12083575 | 0.04613958 | 0.00224551 | 0.11191166 | -0.01613749 | -0.02146923 | 0.03069292 | -0.1651295 | 0.095361137 | -0.08406569 | -0.1566521 | -0.09321140013 | 0.20371895 | 0.1212529 | -0.09577773 | -0.008895018 | -0.05338218 | -0.1516329 | 0.04195436 | 0.1878028 | 0.02743697 | -0.06169235 | 0.009990479 | -0.11222351 | 0.03916014 | 0.009990479 | -0.2014101 | 0.2155984 | -0.11479548 | -0.02437538 |
propionic_acid | 0.05204696 | -0.11126960 | 0.02929166 | -0.02678931 | 0.0952342132 | -0.09459811 | -0.03003317 | -0.03991217 | -0.10476762 | -0.04559440 | 0.01004809 | 0.03538336 | -0.1134535 | 0.029136059 | -0.07622693 | -0.1017626 | -0.00001110557 | 0.22930148 | 0.2051389 | -0.08114750 | 0.053369255 | -0.06856381 | -0.1345117 | 0.01518367 | 0.0229006 | 0.09200223 | -0.07703053 | -0.010252414 | -0.09729968 | 0.06968642 | -0.010252414 | -0.1431086 | 0.2591636 | -0.08610552 | -0.09916577 |
butyric_acid | -0.13604957 | -0.10526382 | -0.16101055 | -0.17232419 | -0.0004175809 | -0.09642060 | -0.01072453 | -0.04490758 | -0.07197388 | -0.04747222 | -0.02421638 | 0.16074285 | -0.2196374 | 0.008502025 | -0.12456361 | -0.1438063 | -0.15658623990 | 0.05946432 | 0.2165128 | -0.10942620 | 0.112840386 | -0.08831867 | -0.1247286 | 0.06561711 | 0.1654345 | -0.03863936 | -0.02175125 | 0.018979201 | -0.16384997 | -0.04482030 | 0.018979201 | -0.2561053 | 0.3480001 | -0.16527575 | -0.07693781 |
scalebluered <- colorRampPalette(brewer.pal(8, "RdBu"))(50)
# Plot correlation
matrix_tax_SCFA <- cor(abundances_fam[, c(3:5)], abundances_fam[,c(16:50)] , method = "spearman")
#corrplot(matrix_tax_SCFA, method="circle", tl.col = "black", tl.srt = 90, col.lim = c(-1,1), is.corr = FALSE)
# I did not like how the generic legend looked like, so I decided to generate legend separately. However,
# I did not know how to put it on right side of the plot to look like the other plots, so I put it on the left side...
corrplot(matrix_tax_SCFA, method="circle", tl.col = "black", tl.srt = 90, cl.pos="n", insig = "blank")
colorlegend(xlim=c(-3,0), ylim=c(10,5), scalebluered, c(seq(-1,1,1)), align="r", vertical=TRUE, addlabels=TRUE)
# Save results as data frame
alpha_SCFA_cor <- as.data.frame(cor(abundances_fam[, c(3:5)], abundances_fam[,c(6:15)]))
alpha_SCFA_cor %>% tibble::rownames_to_column() %>% flextable()
rowname | shannon_entropy | chao1 | fisher_alpha | margalef | gini_index | menhinick | strong | simpson | faith_pd | pielou_evenness |
|---|---|---|---|---|---|---|---|---|---|---|
acetic_acid | -0.2646461 | -0.1095884 | -0.1199726 | -0.1176453 | 0.2153806 | -0.1176453 | 0.13095051 | -0.3855660 | -0.01865583 | -0.303903050 |
propionic_acid | -0.2595886 | -0.1444708 | -0.1557334 | -0.1534482 | 0.2497485 | -0.1534482 | 0.17265440 | -0.2722972 | -0.01298810 | -0.229056041 |
butyric_acid | -0.3157031 | -0.3299432 | -0.3334144 | -0.3327643 | 0.3318925 | -0.3327643 | -0.08957821 | -0.1894455 | -0.27550113 | 0.004129023 |
# Plot correlation
matrix_alpha_SCFA <- cor(abundances_fam[, c(3:5)], abundances_fam[,c(6:15)] , method = "spearman")
corrplot(matrix_alpha_SCFA, method="circle", tl.col = "black", tl.srt = 90, col.lim = c(-1,1), insig = "blank")
matrix_all <- cor(abundances_fam[, c(3:15)], abundances_fam[,c(16:50)] , method = "spearman")
corrplot(matrix_all, method="circle", tl.col = "black", tl.srt = 90, col.lim = c(-1,1), insig = "blank")
# tax_glom function merges species that have the same taxonomy at a certain
# taxonomic rank - in this case genus level
glom <- tax_glom(physeq, taxrank=rank_names(physeq)[6])
# psmelt function melts phyloseq data object into large data.frame
smelted_data <- psmelt(glom)
# Problem with Clostridium!
abundances_gen <- smelted_data %>% select(-c(Kingdom, Phylum, Class, Order, Family)) %>%
spread(Genus, Abundance) %>%
group_by(Sample) %>% select(-c(Clostridium)) %>%
summarize(across(2:94, ~unique(na.omit(.x))),.groups = 'drop')
abundances_gen
## # A tibble: 104 × 94
## Sample peti donor_donation acetic_acid propionic_acid butyric_acid
## <chr> <int> <chr> <dbl> <dbl> <dbl>
## 1 A1-Placa-E2 216133466 CGR32F_7th 336. 77.3 75.8
## 2 A10-Placa-E2 226170254 CLA33F_11th 177. 60.3 163.
## 3 A11-Placa-E2 226175993 MBD34F_3rd 43.7 22.8 24.1
## 4 A12-Placa-E2 226180072 FBG21M_4th 187. 46.0 42.6
## 5 A2-Placa-E2 216133396 RTF49M_4th 52.3 14.2 16.1
## 6 A3-Placa-E1 226185617 SMP48F_6th 47.0 18.6 17.6
## 7 A3-Placa-E2 216136699 RTF49M_10th 369. 131. 87.1
## 8 A4-Placa-E2 216139548 RTF49M_15th 131. 36.4 82.1
## 9 A5-Placa-E2 216142212 EDR39F_1st 126. 67.1 57.8
## 10 A6-Placa-E2 216144512 ATH27F_1st 67.0 32.3 25.3
## # ℹ 94 more rows
## # ℹ 88 more variables: shannon_entropy <dbl>, chao1 <dbl>, fisher_alpha <dbl>,
## # margalef <dbl>, gini_index <dbl>, menhinick <dbl>, strong <dbl>,
## # simpson <dbl>, faith_pd <dbl>, pielou_evenness <dbl>,
## # `[Eubacterium]` <dbl>, `[Ruminococcus]` <dbl>, `1-68` <dbl>,
## # Acidaminococcus <dbl>, Acinetobacter <dbl>, Adlercreutzia <dbl>,
## # AF12 <dbl>, Akkermansia <dbl>, Alistipes <dbl>, Anaerostipes <dbl>, …
write.table(abundances_gen, file = here("01_tidy_data", "abundance_genera.tsv"), row.names=FALSE, sep="\t", quote=FALSE)
# Save results as data frame
tax_alpha_cor <- as.data.frame(cor(abundances_gen[, c(7:16)], abundances_gen[,c(17:94)]))
tax_alpha_cor %>% tibble::rownames_to_column() %>% flextable()
rowname | [Eubacterium] | [Ruminococcus] | 1-68 | Acidaminococcus | Acinetobacter | Adlercreutzia | AF12 | Akkermansia | Alistipes | Anaerostipes | Anaerotruncus | Bacteroides | Barnesiella | Bifidobacterium | Bilophila | Blautia | Butyricicoccus | Butyricimonas | Campylobacter | Catenibacterium | cc_115 | Citrobacter | Collinsella | Coprobacillus | Coprococcus | Dehalobacterium | Desulfovibrio | Dialister | Dorea | Enterobacter | Enterococcus | Epulopiscium | Faecalibacterium | Fusobacterium | Gemmiger | Gluconacetobacter | Granulicatella | Haemophilus | Hafnia | Holdemania | human | Klebsiella | Lachnobacterium | Lachnospira | Lactobacillus | Lactococcus | Megamonas | Megasphaera | Methanobrevibacter | Mitsuokella | Morganella | Odoribacter | Oscillospira | Oxalobacter | Parabacteroides | Paraprevotella | Peptococcus | Phascolarctobacterium | Porphyromonas | Prevotella | Pseudomonas | Pseudoramibacter_Eubacterium | rc4-4 | RFN20 | Rikenella | Roseburia | Ruminococcus | Serratia | Slackia | SMB53 | Sneathia | Streptococcus | Sutterella | Synergistes | Turicibacter | Veillonella | WAL_1855D | Weissella |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
shannon_entropy | 0.07159998 | 0.13938767 | 0.23103013 | 0.108286334 | 0.036780567 | 0.068457389 | 0.17354547 | 0.21747245 | 0.48221400 | -0.01550384 | 0.23152449 | -0.10402188 | 0.04431397 | 0.11404702 | 0.27230601 | -0.07156724 | 0.06095575072 | 0.452660506 | -0.13617509 | -0.270733340 | 0.30015993 | 0.02763261 | 0.14846651 | 0.01307427 | 0.27728119 | 0.16634117 | 0.39709750 | -0.075214784 | 0.11158385 | 0.06751459 | 0.11363339 | 0.057805254 | -0.23290899 | 0.09246265 | -0.05628918 | 0.03779447 | 0.08882543 | 0.035661043 | 0.09788973 | -0.09241026 | 0.309043913 | 0.06408121 | 0.32438746 | 0.0002913416 | 0.05627490 | -0.15010474 | 0.18472891 | 0.15326186 | 0.42413481 | 0.17225303 | -0.03861396 | 0.18666254 | 0.4686748 | 0.3966001 | 0.18359537 | -0.10191302 | 0.18119343 | 0.033820084 | 0.08170784 | 0.2165781 | 0.015380381 | 0.04727198 | 0.25905638 | 0.08918314 | -0.14074391 | -0.06853381 | 0.26377240 | 0.03423626 | 0.229274107 | -0.08552451 | 0.01477416 | -0.007667943 | 0.012886096 | 0.19638858 | -0.052283432 | -0.2861082 | 0.13175347 | 0.036780567 |
chao1 | -0.03638702 | 0.10205368 | 0.21274291 | 0.152584970 | 0.042111939 | -0.021874857 | 0.31611978 | 0.36348536 | 0.52420789 | -0.16313867 | 0.13168898 | 0.06077046 | 0.06291673 | 0.14902624 | 0.30325114 | -0.05674697 | 0.07743809648 | 0.698884646 | -0.05413649 | -0.272253842 | 0.33423134 | -0.06743896 | 0.18521457 | 0.09730856 | 0.39460160 | 0.21082246 | 0.41982657 | -0.088170642 | 0.04342752 | 0.01427595 | 0.12923304 | 0.091035791 | -0.35887258 | 0.03090747 | -0.02826961 | -0.04645710 | 0.06547280 | -0.003174261 | 0.03220064 | -0.16174144 | 0.263675376 | 0.11035859 | 0.26796493 | -0.0789801950 | 0.14336458 | -0.09338715 | 0.14848375 | 0.18019220 | 0.38925318 | 0.20769049 | -0.11731234 | 0.32352868 | 0.5775615 | 0.5081410 | 0.22001099 | -0.11927104 | 0.15345588 | 0.018964675 | 0.02210724 | 0.3270622 | -0.078345476 | -0.01609057 | 0.32736930 | 0.04514859 | -0.05404873 | -0.13528621 | 0.34206429 | -0.01356003 | 0.238517312 | -0.02537611 | -0.02351381 | -0.022595562 | -0.015945179 | 0.26277538 | -0.053687155 | -0.2089988 | 0.06692396 | 0.042111939 |
fisher_alpha | -0.04266201 | 0.10243623 | 0.22777165 | 0.142881861 | 0.028522431 | -0.018170692 | 0.30695543 | 0.36372284 | 0.52843491 | -0.17079839 | 0.13419861 | 0.05441420 | 0.04653088 | 0.14663316 | 0.30520335 | -0.06533926 | 0.06058732764 | 0.705909829 | -0.05118035 | -0.284136402 | 0.34014791 | -0.06547499 | 0.18610876 | 0.10918235 | 0.39736206 | 0.21765952 | 0.43297201 | -0.104391958 | 0.04544028 | 0.01023980 | 0.13301278 | 0.073548985 | -0.35961444 | 0.03711979 | -0.03201998 | -0.04366895 | 0.06909077 | -0.009185043 | 0.03640441 | -0.15871957 | 0.276935541 | 0.09784401 | 0.27146610 | -0.0826432096 | 0.14914291 | -0.09628639 | 0.15289732 | 0.18495988 | 0.40319678 | 0.20402245 | -0.11322640 | 0.31929618 | 0.5838954 | 0.5168397 | 0.21710880 | -0.13397330 | 0.15784148 | 0.027229629 | 0.02004396 | 0.3207720 | -0.074451843 | -0.01817683 | 0.32360956 | 0.03903789 | -0.05125168 | -0.13404434 | 0.34823021 | -0.01303907 | 0.248360533 | -0.02453051 | -0.02197679 | -0.029756605 | -0.019397709 | 0.26766104 | -0.070188588 | -0.2262530 | 0.07148311 | 0.028522431 |
margalef | -0.04294028 | 0.10703291 | 0.22081353 | 0.147170247 | 0.030786743 | -0.014988000 | 0.30635207 | 0.36329867 | 0.52660033 | -0.16756017 | 0.13279219 | 0.05467900 | 0.04908215 | 0.15119899 | 0.31168381 | -0.06455511 | 0.06160509981 | 0.703323138 | -0.04968787 | -0.285537297 | 0.33033472 | -0.06380222 | 0.18849984 | 0.10661453 | 0.39602264 | 0.21862052 | 0.42764732 | -0.098549087 | 0.04850559 | 0.01256500 | 0.13466851 | 0.075039558 | -0.35843293 | 0.03958950 | -0.02837994 | -0.04210025 | 0.06813527 | -0.010093940 | 0.03859606 | -0.15337586 | 0.271504546 | 0.10022254 | 0.26794237 | -0.0844359241 | 0.15189829 | -0.09583334 | 0.15123247 | 0.18654035 | 0.39658681 | 0.20843923 | -0.11498723 | 0.31896261 | 0.5851950 | 0.5137065 | 0.21497119 | -0.13619450 | 0.15573587 | 0.026531909 | 0.02187530 | 0.3276695 | -0.073015363 | -0.01606918 | 0.31517779 | 0.04119917 | -0.04990957 | -0.12627784 | 0.34971356 | -0.01086296 | 0.246135995 | -0.02197471 | -0.01941388 | -0.026716509 | -0.015737951 | 0.25725703 | -0.067240540 | -0.2252004 | 0.07290958 | 0.030786743 |
gini_index | -0.04878789 | -0.14172151 | -0.27101405 | -0.124796782 | -0.026077484 | -0.039736261 | -0.24861298 | -0.25221615 | -0.51722967 | 0.06726804 | -0.23208294 | 0.03201768 | -0.03675671 | -0.11179463 | -0.28727367 | 0.06540978 | -0.08547496357 | -0.554753489 | 0.09933723 | 0.286216292 | -0.32914016 | -0.01431225 | -0.15083960 | -0.05752248 | -0.36608418 | -0.16334157 | -0.40605757 | 0.120295470 | -0.10668560 | -0.05076923 | -0.10099551 | -0.049507254 | 0.26796761 | -0.06774699 | 0.06275676 | -0.02455684 | -0.08644533 | -0.021119345 | -0.08923833 | 0.10308008 | -0.324204596 | -0.04836574 | -0.33604171 | -0.0005443647 | -0.06992236 | 0.14100810 | -0.19708097 | -0.12450000 | -0.46017354 | -0.14386411 | 0.05044059 | -0.28083386 | -0.5142416 | -0.4275486 | -0.23115889 | 0.12565482 | -0.19431764 | -0.024596955 | -0.06700058 | -0.1814911 | 0.002865844 | -0.03869648 | -0.28919881 | -0.08152186 | 0.10261073 | 0.09975348 | -0.33282357 | -0.03122341 | -0.239554579 | 0.08815003 | 0.00722504 | 0.012485752 | -0.001674808 | -0.26427198 | 0.063402678 | 0.2891960 | -0.12184022 | -0.026077484 |
menhinick | -0.04294028 | 0.10703291 | 0.22081353 | 0.147170247 | 0.030786743 | -0.014988000 | 0.30635207 | 0.36329867 | 0.52660033 | -0.16756017 | 0.13279219 | 0.05467900 | 0.04908215 | 0.15119899 | 0.31168381 | -0.06455511 | 0.06160509981 | 0.703323138 | -0.04968787 | -0.285537297 | 0.33033472 | -0.06380222 | 0.18849984 | 0.10661453 | 0.39602264 | 0.21862052 | 0.42764732 | -0.098549087 | 0.04850559 | 0.01256500 | 0.13466851 | 0.075039558 | -0.35843293 | 0.03958950 | -0.02837994 | -0.04210025 | 0.06813527 | -0.010093940 | 0.03859606 | -0.15337586 | 0.271504546 | 0.10022254 | 0.26794237 | -0.0844359241 | 0.15189829 | -0.09583334 | 0.15123247 | 0.18654035 | 0.39658681 | 0.20843923 | -0.11498723 | 0.31896261 | 0.5851950 | 0.5137065 | 0.21497119 | -0.13619450 | 0.15573587 | 0.026531909 | 0.02187530 | 0.3276695 | -0.073015363 | -0.01606918 | 0.31517779 | 0.04119917 | -0.04990957 | -0.12627784 | 0.34971356 | -0.01086296 | 0.246135995 | -0.02197471 | -0.01941388 | -0.026716509 | -0.015737951 | 0.25725703 | -0.067240540 | -0.2252004 | 0.07290958 | 0.030786743 |
strong | -0.11188448 | -0.08337943 | -0.04996814 | 0.071174960 | 0.019243860 | -0.096462430 | 0.11713086 | 0.30594809 | 0.12292211 | -0.25971058 | -0.21268317 | 0.11517161 | 0.04135788 | 0.11523776 | 0.11241541 | -0.03837496 | -0.04857870484 | 0.407033975 | 0.10206079 | -0.001743082 | 0.06678907 | -0.20773467 | 0.14316523 | 0.13947974 | 0.06207966 | 0.19784778 | 0.20260374 | 0.067816446 | -0.15198084 | -0.06290857 | 0.11663887 | 0.066683353 | -0.31387998 | -0.01563013 | 0.08471928 | -0.15735407 | 0.01395815 | -0.053582330 | -0.09304711 | -0.18367770 | -0.004601054 | 0.16825930 | -0.05350426 | -0.2683619423 | 0.17218141 | 0.10346468 | -0.04239236 | 0.20109981 | -0.01445655 | 0.20442597 | -0.20031183 | 0.09894205 | 0.2817832 | 0.2829366 | -0.04764457 | -0.01478512 | -0.02263729 | 0.031020173 | -0.04906963 | 0.4168351 | -0.173196574 | -0.14083349 | 0.09150597 | -0.08175925 | 0.10619220 | -0.11240150 | 0.08556134 | -0.10744658 | 0.092844612 | 0.15272963 | -0.01629158 | -0.001553990 | -0.049059400 | -0.01111107 | -0.009895018 | 0.1337865 | -0.04518166 | 0.019243860 |
simpson | 0.17206462 | 0.06577147 | 0.15170291 | 0.005033255 | 0.035672617 | 0.115782331 | -0.08907821 | 0.01158831 | 0.26524339 | 0.14128105 | 0.22033065 | -0.29376672 | 0.02580022 | 0.02676426 | 0.08618909 | -0.06359497 | -0.00004246016 | -0.002365089 | -0.24701477 | -0.118277906 | 0.20002527 | 0.06446741 | 0.05925141 | -0.12882887 | -0.03998642 | 0.08488361 | 0.28448218 | 0.008442535 | 0.07707192 | 0.08907522 | 0.07548602 | 0.036444531 | -0.05762422 | 0.11583283 | -0.07036063 | 0.06613545 | 0.08533862 | 0.094908668 | 0.10397670 | -0.07280287 | 0.258577001 | 0.04081203 | 0.26724234 | 0.0528378731 | -0.05713842 | -0.15884818 | 0.13461960 | 0.12737346 | 0.29645593 | 0.11718767 | 0.04140618 | -0.13191872 | 0.1618745 | 0.1856331 | 0.03938481 | 0.02939851 | 0.13051522 | 0.050686613 | 0.09772102 | 0.1067618 | 0.063874585 | 0.06359883 | 0.15685844 | 0.09001612 | -0.25339392 | -0.01804240 | -0.02631759 | 0.03298194 | 0.141150275 | -0.10125470 | 0.04775054 | -0.009406021 | 0.018318426 | 0.07519729 | -0.020617179 | -0.2214215 | 0.12461393 | 0.035672617 |
faith_pd | 0.11948764 | 0.03200218 | 0.13900974 | 0.287049979 | -0.054986273 | -0.005281073 | 0.32182268 | 0.37658481 | 0.23631863 | -0.33942636 | 0.06903994 | -0.03442819 | -0.02319745 | 0.20266925 | 0.22381638 | -0.03717315 | 0.11658230895 | 0.542337613 | -0.02828822 | -0.091551030 | 0.23064248 | -0.12478391 | 0.27069566 | 0.06733520 | 0.27548528 | 0.15031176 | 0.41544342 | -0.092222016 | 0.04536866 | -0.03616911 | 0.15630988 | 0.003829546 | -0.45481567 | 0.03968340 | -0.02106906 | -0.09688830 | 0.04559428 | -0.136334961 | 0.01215433 | -0.27508335 | 0.305044126 | 0.17997298 | 0.15965525 | -0.2860212562 | 0.08073983 | -0.08821139 | 0.14449164 | 0.13522310 | 0.35482468 | 0.03901185 | -0.08556328 | 0.15483481 | 0.2881591 | 0.3597795 | 0.07753525 | 0.02526113 | 0.14154497 | -0.004425807 | 0.06395975 | 0.1933990 | -0.128385848 | -0.03580521 | 0.19379312 | 0.05027771 | -0.03145027 | -0.25646404 | 0.24383624 | 0.02773202 | 0.224224377 | -0.01229593 | -0.06119944 | -0.022356535 | -0.137494964 | 0.12863566 | -0.116453816 | -0.1157593 | 0.10119138 | -0.054986273 |
pielou_evenness | 0.21042975 | 0.03011787 | 0.08322478 | -0.095873353 | -0.003949148 | 0.132002879 | -0.21863064 | -0.24030542 | -0.02679162 | 0.24755163 | 0.20908765 | -0.30487445 | -0.02237424 | -0.09177427 | -0.10673545 | -0.02812479 | -0.01307993607 | -0.396300680 | -0.18934919 | 0.010096994 | 0.03938567 | 0.15696295 | -0.08077847 | -0.15894402 | -0.18496708 | -0.08720601 | 0.01403213 | -0.013154554 | 0.10293579 | 0.08648484 | -0.03802944 | -0.035991315 | 0.19715646 | 0.08480880 | -0.09139849 | 0.13624348 | 0.04902762 | 0.085048126 | 0.09819751 | 0.05689466 | 0.129180976 | -0.07826021 | 0.15076665 | 0.1700677747 | -0.18446494 | -0.12177272 | 0.08683748 | -0.05591838 | 0.13015699 | -0.08073323 | 0.15665210 | -0.23306289 | -0.1891298 | -0.1521718 | -0.03081689 | 0.06859167 | 0.07559217 | 0.016824346 | 0.09874500 | -0.2303185 | 0.150463629 | 0.10166737 | -0.01771059 | 0.07734198 | -0.19641210 | 0.04219254 | -0.15136302 | 0.06647489 | 0.003835268 | -0.14854419 | 0.04095021 | 0.002504481 | 0.024317169 | -0.02002618 | -0.008113092 | -0.1549767 | 0.10538298 | -0.003949148 |
# Plot correlation
matrix_tax_alpha_1 <- cor(abundances_gen[, c(7:16)], abundances_gen[,c(17:55)] , method = "spearman")
corrplot(matrix_tax_alpha_1, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
matrix_tax_alpha_2 <- cor(abundances_gen[, c(7:16)], abundances_gen[,c(56:94)] , method = "spearman")
corrplot(matrix_tax_alpha_2, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
# Save results as data frame
tax_SCFA_cor <- as.data.frame(cor(abundances_gen[, c(4:6)], abundances_gen[,c(17:94)]))
tax_SCFA_cor %>% tibble::rownames_to_column() %>% flextable()
rowname | [Eubacterium] | [Ruminococcus] | 1-68 | Acidaminococcus | Acinetobacter | Adlercreutzia | AF12 | Akkermansia | Alistipes | Anaerostipes | Anaerotruncus | Bacteroides | Barnesiella | Bifidobacterium | Bilophila | Blautia | Butyricicoccus | Butyricimonas | Campylobacter | Catenibacterium | cc_115 | Citrobacter | Collinsella | Coprobacillus | Coprococcus | Dehalobacterium | Desulfovibrio | Dialister | Dorea | Enterobacter | Enterococcus | Epulopiscium | Faecalibacterium | Fusobacterium | Gemmiger | Gluconacetobacter | Granulicatella | Haemophilus | Hafnia | Holdemania | human | Klebsiella | Lachnobacterium | Lachnospira | Lactobacillus | Lactococcus | Megamonas | Megasphaera | Methanobrevibacter | Mitsuokella | Morganella | Odoribacter | Oscillospira | Oxalobacter | Parabacteroides | Paraprevotella | Peptococcus | Phascolarctobacterium | Porphyromonas | Prevotella | Pseudomonas | Pseudoramibacter_Eubacterium | rc4-4 | RFN20 | Rikenella | Roseburia | Ruminococcus | Serratia | Slackia | SMB53 | Sneathia | Streptococcus | Sutterella | Synergistes | Turicibacter | Veillonella | WAL_1855D | Weissella |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
acetic_acid | -0.048231715 | 0.1544897 | -0.1102867 | 0.13862046 | 0.009990479 | -0.02676645 | 0.16799779 | 0.13478994 | -0.2750128 | -0.07243646 | -0.1364766 | 0.11191741 | -0.008353112 | -0.01613749 | 0.01269479 | 0.15646609 | 0.14005715 | -0.01370241 | -0.02146923 | 0.1388464 | -0.1324437 | 0.0437654 | -0.06968238 | -0.06124696 | 0.1291944 | -0.1566521 | -0.10066299 | 0.2395926 | 0.01444078 | 0.08974546 | -0.09577773 | -0.02618438 | 0.15406588 | -0.1516329 | 0.1813651 | 0.06470166 | 0.03069292 | 0.2155984 | -0.04863183 | -0.02589902 | -0.2252298 | 0.18563814 | -0.1757955 | 0.11992883 | 0.02743697 | 0.2371008 | -0.11117575 | -0.122929703 | -0.11222351 | -0.11731467 | -0.06654224 | 0.24937286 | -0.08860194 | -0.2014101 | 0.001515321 | 0.0408958294 | -0.10698489 | -0.10590844 | -0.09910456 | 0.03855663 | 0.05254562 | -0.05338218 | -0.09030307 | -0.09721057 | -0.01654294 | 0.2908791 | 0.166630062 | -0.03145050 | -0.002093324 | 0.1543014 | -0.06169235 | 0.2088887 | 0.04613958 | -0.02808312 | 0.02228463 | 0.1432133 | -0.10890530 | 0.009990479 |
propionic_acid | -0.005735281 | 0.1266747 | -0.1001720 | -0.02788658 | -0.010252414 | -0.04976517 | 0.01861533 | 0.09966111 | -0.1973662 | -0.02520465 | -0.1224400 | -0.10476337 | -0.006627257 | -0.04559440 | 0.04907994 | 0.06281714 | 0.09146129 | -0.12609920 | 0.01004809 | 0.2112414 | -0.1467473 | 0.0460600 | -0.05305150 | -0.02237027 | -0.1147851 | -0.1017626 | -0.01367881 | 0.3995076 | 0.01840001 | 0.10654161 | -0.08114750 | -0.00475195 | 0.08658573 | -0.1345117 | 0.1680536 | 0.09640637 | 0.03538336 | 0.2591636 | -0.03841114 | -0.10965634 | -0.1985604 | 0.20207626 | -0.1937272 | -0.01866294 | 0.09200223 | 0.2969093 | -0.09717652 | 0.001720114 | -0.09729968 | 0.01532995 | -0.06424677 | 0.04566383 | -0.08370994 | -0.1431086 | -0.139153838 | 0.0952342132 | -0.09406458 | -0.12919530 | -0.06966460 | 0.23646185 | 0.07792443 | -0.06856381 | -0.13788048 | -0.08440119 | 0.01392033 | 0.2594391 | -0.008833628 | -0.02459244 | -0.008608915 | 0.1236279 | -0.07703053 | 0.2725172 | -0.03003317 | -0.08722848 | 0.03776054 | 0.2193534 | -0.08368842 | -0.010252414 |
butyric_acid | -0.058493438 | 0.1239715 | -0.1055359 | -0.08559811 | 0.018979201 | -0.02814483 | -0.07869090 | -0.03782660 | -0.2344429 | 0.11569087 | -0.1551789 | -0.07196801 | -0.096788329 | -0.04747222 | -0.05143746 | 0.04416191 | 0.10036190 | -0.28548307 | -0.02421638 | 0.1621426 | -0.1473870 | 0.1204202 | -0.09024779 | -0.05457181 | -0.1499684 | -0.1438063 | -0.13759479 | 0.3160254 | 0.04932059 | 0.04830233 | -0.10942620 | -0.05041052 | 0.34579200 | -0.1247286 | 0.2825893 | 0.16983778 | 0.16074285 | 0.3480001 | -0.06554484 | 0.01971079 | -0.2149490 | 0.04000696 | -0.1533753 | 0.11134722 | -0.03863936 | 0.4003416 | -0.10839353 | -0.062927225 | -0.16384997 | -0.04191171 | -0.06476452 | -0.04890160 | -0.22153577 | -0.2561053 | -0.104676715 | -0.0004175809 | -0.10395799 | -0.06268824 | -0.07022972 | 0.04870113 | 0.16002676 | -0.08831867 | -0.13235299 | -0.09046454 | -0.02115347 | 0.3575807 | -0.003415168 | -0.03250106 | -0.074563052 | 0.1551168 | -0.02175125 | 0.2833861 | -0.01072453 | -0.07077105 | 0.11348622 | 0.2325765 | -0.08491102 | 0.018979201 |
# Plot correlation
matrix_tax_SCFA_1 <- cor(abundances_gen[, c(4:6)], abundances_gen[,c(17:55)] , method = "spearman")
corrplot(matrix_tax_SCFA_1, method="circle", tl.col = "black", tl.srt = 90, cl.pos="n", insig = "blank")
colorlegend(xlim=c(-3,0), ylim=c(10,5), scalebluered, c(seq(-1,1,1)), align="r", vertical=TRUE, addlabels=TRUE)
matrix_tax_SCFA_2 <- cor(abundances_gen[, c(4:6)], abundances_gen[,c(56:94)] , method = "spearman")
corrplot(matrix_tax_SCFA_2, method="circle", tl.col = "black", tl.srt = 90, cl.pos="n", insig = "blank")
colorlegend(xlim=c(-3,0), ylim=c(10,5), scalebluered, c(seq(-1,1,1)), align="r", vertical=TRUE, addlabels=TRUE)
matrix_all_1 <- cor(abundances_gen[, c(4:16)], abundances_gen[,c(17:55)] , method = "spearman")
corrplot(matrix_all_1, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
matrix_all_2 <- cor(abundances_gen[, c(4:16)], abundances_gen[,c(56:94)] , method = "spearman")
corrplot(matrix_all_2, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
abund_fam <- abundances_fam[,3:62]
abund_fam <- abund_fam[, -c(4:13)]
testRes_fam = cor.mtest(abund_fam, conf.level = 0.95)
matrix_fam <- cor(abund_fam, method = "spearman")
corrplot(matrix_fam, p.mat = testRes_fam$p, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
# table of p-values
P_val_fam <- as.data.frame(testRes_fam$p)
P_val_fam <- P_val_fam[-c(4:50), -c(1:3)]
P_val_fam <- tibble::rownames_to_column(P_val_fam, "SCFA")
# export table
write_xlsx(P_val_fam, here("03_plots_and_tables", "correlation_p_val_family.xlsx"))
abund_gen_1 <- abundances_gen[,4:55]
abund_gen_1 <- abund_gen_1[, -c(4:13)]
testRes_gen_1 <- cor.mtest(abund_gen_1, conf.level = 0.95)
matrix_gen_1 <- cor(abund_gen_1, method = "spearman")
corrplot(matrix_gen_1, p.mat = testRes_gen_1$p, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
# table of p-values
P_val_gen_1 <- as.data.frame(testRes_gen_1$p)
P_val_gen_1 <- P_val_gen_1[-c(4:42), -c(1:3)]
abund_gen_2 <- abundances_gen[,4:94]
abund_gen_2 <- abund_gen_2[, -c(4:52)]
testRes_gen_2 <- cor.mtest(abund_gen_2, conf.level = 0.95)
matrix_gen_2 <- cor(abund_gen_2, method = "spearman")
#pdf("my_plot.pdf")
corrplot(matrix_gen_2, p.mat = testRes_gen_2$p, method="circle", tl.col = "black", tl.srt = 90, tl.cex =0.9, col.lim = c(-1,1), insig = "blank")
#dev.off()
# table of p-values
P_val_gen_2 <- as.data.frame(testRes_gen_2$p)
P_val_gen_2 <- P_val_gen_2[-c(4:42), -c(1:3)]
# merge tables
p_val_gen_all <- cbind(P_val_gen_1, P_val_gen_2)
p_val_gen_all <- tibble::rownames_to_column(p_val_gen_all, "SCFA")
# export table
write_xlsx(p_val_gen_all, here("03_plots_and_tables", "correlation_p_val_genus.xlsx"))